Solving Dirty Data through High-Quality Outsourcing

Data is as valuable as gold to many companies, representing its potential long-term financial value. Good data quality provides ways to improve efficiency, reduce risk, and even cost. Dirty data needs to be cleaned and properly structured to make it of practical use for companies. Unclean data can contaminate accuracy and compromise systems. Even mere manual data entry can introduce human errors into the mix. The importance of retrieving clean data is paramount to proper handling of it. In business process outsourcing, knowing how to do effective data cleansing and enrichment can put companies at the forefront of their industry.

Three Harmful Data Types to Every Business

In 2018 alone, there were as many as 2.5 quintillion bytes of data processed. This data is growing more every year and expected to grow to as much as 175 zettabytes by 2025. This is big data, and it is easy to contaminate with dirty data. Poor data quality can come from inaccurate, incorrect, or misleading information. Duplicates, data that violate rules, and misspelled and badly punctuated data is still dirty data. Apart from dirty data, there’s also dark data and unstructured data. Dark data is information not in use, while unstructured data is information not prepared for use.

Mining all of this data and keeping it compliant, consistent and clean can be overwhelming and costly. Data outsourcing is crucial in handling all three data types. Businesses across different industries need to know how to process this data to improve business processes.

What Leads to Dirty Data?

With the existence of dirty data and bad CRM data, a question remains: how does it proliferate? The biggest challenge to dirty data proliferation is human error. How can bad data entry pollute a data pool? Inaccurate, incorrect, misleading data compounds with duplications, data that violate rules, and misspelled or poorly punctuated data. When building data at a BPO level, there are ways to address data quality upfront. Most BPO organizations and developers can provide tools that conduct accurate data merging. Even then, data outsourcing would still need to work on areas impossible to automate. These include regional spellings, duplicates, date-time formats, and word cases.

With this in mind, it’s crucial to execute clean data practices. Systems like the Internet of Things (IoT) use trust, identity, and chain of custody can help make sure data is clean. Trust confirms that devices are talking to the right devices and systems. Identity confirms that upcoming data has correct parameters, and the right device sent it. Chain of custody creates an understanding of the history of its data points. Data still runs by the law of garbage-in, garbage-out. Good data entry needs to happen to prevent dirty data from contaminating data quality.

Steps for Cleaning and Structuring Your Data

So, how do companies update and clean data in their systems? There are three steps for creating clean, structured data with clear potential:

  • Standardized tracking and recording of datasets
  • Clear data addition and integration
  • BPO workforce planning

First, businesses need to create an internal standard of sorting, cataloging, and managing data. Companies need to have a sense for the gold standard for data quality. Data outsourcing needs to anticipate potential regulations, laws, and processes with which the team needs to comply. Once the standard is ready, disseminate the information and educate employees from top to bottom. Next, CRM data integration needs to focus on processes crucial to profitability. Every layer of the company’s tech stack needs careful examination for what gives the most ROI. This can be the speed of processing, accuracy, or even volume of data.

Once the company pinpoints this process, stack alignment follows. The tech stack needs to address data quality issues and allow business process outsourcing to handle the data. With everything in place, the company needs to plan how its workforce will process the data. Anything that the tech stack cannot automate will go to the human labor team. This typically includes quality control, technology gaps, and exceptions. The structure of the BPO team will need to have core teams that handle these outliers. There should also be teams that specialize in handling functions the core team cannot manage.

How Can You Improve Data Quality and Eliminate Dirty Data?

To resolve the issue of dirty data, the best answer is to find a business process outsourcing partner that does the job properly. Outsourcing offers many different advantages over using in-house personnel. While existing in-house teams may effective at improving data quality, the sheer cost and operational needs can team kill profitability. Business process outsourcing can manage massive, consistent data pipelines for large companies. Enterprise businesses can clear CRM data en masse with very little to zero loss in data quality. The right BPO team can provide the level of agility an enterprise needs.

In the long run, the goal should be to build machine learning capabilities to handle structured data. A machine that can learn from human expertise can make data processing faster, too. There are many ways to teach machines how to utilize structured training data and help them learn. These can come from public datasets, pre-trained models, embedded labeling tasks, and combining free data with company data.

Assivo Knows How to Handle Your Data

If your company wants to clean and mine dirty data, it’s crucial to know proper strategies. Clean, structured, visible data is critical to helping businesses achieve explosive growth. Companies need to have a standard for handling CRM data, improving data quality, and entering data properly.

Assivo provides reliable, cost-effective business process outsourcing. Data entry comes not only from managed offshore teams that ensure data quality but also process automation. Assivo brings the best people together with the best standards for data entry outsourcing. Every process used is robust, delivering accurate, correct, and usable data. Whatever your company needs to grow, Assivo can provide scalable solutions, from research and data collection to monitoring competition. Assivo is there to provide only the best quality support to every client. Get in touch with us today and find out how you can utilize our core services to your advantage.

About Assivo

Founded in 2016, Assivo is an innovative and agile outsourcing partner to our clients. We assemble fully managed offshore teams tailored to fit individual client requirements.

Over the years, we have developed deep business process and technology expertise from serving 200+ clients. We are focused and dedicated to our clients’ success, and our long-term partnerships have enabled our clients to compete more effectively and win.

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